Extreme Perspectives: The X Games Meets Social Data

Summer has come to Austin and that means a new, somewhat rowdy out-of-town guest visited this weekend. If you woke up Friday morning with a sudden urge to drain your pool, dust off your old Powell Peralta skateboard, and put some Urban Dance Squad on your outdoor speakers -  you can thank the X Games.  

The X Games have been at the epicenter of action sports for almost two decades. The summer X Games include sports such as skateboarding, motocross, off road truck racing, BMX, and now even video games. Since the competition’s inception, the games have been a force in the sports world for athletes and sponsors alike. For the past two years the summer X Games have taken place in Los Angeles, but this weekend they made their first appearance in Austin.

Just like the Texas heat, social buzz continued to rise as we hit the weekend, recording fever peaks on Twitter when medals were won and performances hit the stage. Kanye West, The Flaming Lips, Gary Clark Jr., and Pretty Lights kept crowds tweeting all through the night following bursts of social chatter when participants won or lost.  

Today we’ll take a look at the X Games social data and examine different approaches to getting insights from one, big set of analytics. Are you stoked? Sweet.  

Big Air, Big Opportunities

As I was looking through social media examples of the X Games, I noticed something interesting about the perspective of many of the photos. In many cases, different views of the same event or venue resulted in completely different takeaways. Let me show you an example.

Above is an Instagram post from the X Games account of a big air ramp under construction from this year’s Austin games. That doesn’t look that bad, right? I’m not a big skateboarder, but I bet I could fly down that thing. I could totally do that - piece of cake. Great. That’s Perspective #1.   So let’s look at the same type of ramp, but from a different point of view. Let’s look at it from Perspective #2: the athlete’s point of view.

Nope. No way. Not going to happen. Did anyone else just have a panic attack?

When we look at the same thing from two different angles the takeaways can be night and day. It’s the same ramp, but Perspective #2 gave me a lot more information about why I don’t want to be anywhere near the top of that thing. And now here at Spredfast we’ve got a way to look at social data from different points of view as well.  


Segmentation in Action

Picture yourself as the head of social media for an X Games sponsor, waking up Sunday morning to take a pulse of what people are talking about related to the games. Since Thursday, a non-stop lineup of action sports, video game competitions, and A-list music acts have been thrilling a nationwide audience. You’re looking to craft a post that jumps in on the relevant conversation of the morning, and you check to see the main trending subjects around the event.

You see the following list of topics pop up, which is the actual list of terms that were trending Sunday morning around the X Games: high-level

This is great - you now have a high-level view of what the entire X Games audience is talking about, and what are the hot topics your brand can jump on to have a relevant conversation with the audience. But there’s a good mix of content in here - everything from Kanye West (music) to #skateboarding and #bmx (action sports) to #opticnation (video game competition). If you, as the social media lead, want to join the conversation that your followers are having, how do you know which topic to choose? Which of these topics are resonating with your audience?

What we need to do is go one level deeper. What if we could look at the same set of data through a few different lenses to understand what resonates with specific groups? Adding this view of the data from different perspectives helps us to understand that within every audience there are actually a number of sub-groups talking about slightly different topics. By using a different perspective, you can extract much, much more intelligence from the same set of data, and your social efforts can become relevant to not only the overall event, but your specific audience.    


Spark to the Rescue

We just built an awesome tool called Spark that helps pinpoint patterns in social conversation and the content that is being generated around an event, topic, or trend. It’s a slick way to identify in-the-moment trends and pull in tons of information around the content, accounts, and high-frequency terms/hashtags about each topic, like the X Games.

But one of the coolest features is the ability to look at social data around trends from, you guessed it, a certain point of view. spark_xgames

Spark's trend tracking and identification capabilities give users a follower-based view of any given conversation - or said differently: I understand how everyone is talking about a subject, but what are my followers talking about? And what are the followers of my competition talking about? Will this new lens help us gain insights on how to best take action in social media based on our audience? I bet it will.  

Perspective is Everything

So let’s go back to our Sunday morning exercise and use Spark to not only look at the top trending topics for the entirety of the X Games, but for the followers of three different sponsors. Or said a different way, what’s the relevant conversation that’s happening for each sub-group within the larger X Games audience?

I used the Spark tool to grab trending topics for the followers of three X Games sponsors (GoPro, Ford, and Monster Energy) to see how the trending patterns changed between each audience. I then made a quick Excel table to highlight the different patterns in the data.    



As you can see, distinct categories of conversation (action sports, music, video games) are resonating with each audience. Sponsors' social media teams will find that these varied patterns can be used to create content that's more relevant to their follower base.


After seeing Kanye West at the top of X Games overall Twitter conversation, GoPro’s social media team might be tempted to Tweet about what a great show he put on Saturday night. But by checking the conversation happening with GoPro’s followers, we see that they should probably avoid the music topic and stick to action sports-related posts.


If you’re Ford’s social media team, you would want to jump on the Kanye West conversation Sunday morning to create content that is relevant for your specific follower base. Five of the top ten trending topics (“Donald Trump” is actually a song by Mac Miller, who also performed Saturday night) were music-based, so crafting some strong music-related content should resonate with their X Games followers.

Monster Energy

Monster is seeing the same overall conversation, but with a slightly different concentration compared to the other sponsors. Monster Energy's Twitter followers are talking about action sports in high frequency, but their social media team should also pepper in some content related to the X Games video game competition since followers are chatting about #opticNation and #boysinblue, both video gaming competitors at the event.  

Extreme Insights

Marketing with in-the-moment messaging has been on the rise over the past few years, with brands building out teams, processes, and technology to identify trends and stay relevant to each day’s conversation. As social media teams work to be first at the scene, they must bear in mind that relevancy is key to establishing social connections. High-level topics around an event can pinpoint top terms and phrases, patterns of conversation, and the most popular content - all essentials to being a marketer in today's environment. But adding a hyper-targeted view of a brand's audience can more effectively distribute messaging to the right people at the right time in the right place. All of which is, in analytics terms, totally gnarly, brah.

Chris Kerns's picture

Chris Kerns

Chris Kerns has spent more than a decade defining digital strategy and is at the forefront of finding insights from digital data. He currently leads Analytics and Research at Spredfast. His research has appeared in The New York Times, Forbes, USA Today and AdWeek, among other publications.